This paper introduces the Asynchronous Differential Evolution (ADE) scheme which generalizes the classical Differential Evolution (DE) approach along the dimension of Synchronization Degree (SD). SD regulates the synchrony of the evolution of the current population, i.e. how fast it is replaced by the newly generated population. The definition of the ADE scheme is given and different synchronization strategies are discussed. The introduction of SD parameter allows the tuning of the differential evolution from a completely asynchronous behavior to a super-synchronous behavior. Experiments show that a low SD generally improves the convergence speed and the convergence probability with respect to the classical synchronous DE. Moreover the ordering strategies introduced in ADE seem to improve the performances of the only already known asynchronous variant of DE (the Dynamical Differential Evolution Strategy)
Asynchronous differential evolution
MILANI, Alfredo;SANTUCCI, VALENTINO
2010
Abstract
This paper introduces the Asynchronous Differential Evolution (ADE) scheme which generalizes the classical Differential Evolution (DE) approach along the dimension of Synchronization Degree (SD). SD regulates the synchrony of the evolution of the current population, i.e. how fast it is replaced by the newly generated population. The definition of the ADE scheme is given and different synchronization strategies are discussed. The introduction of SD parameter allows the tuning of the differential evolution from a completely asynchronous behavior to a super-synchronous behavior. Experiments show that a low SD generally improves the convergence speed and the convergence probability with respect to the classical synchronous DE. Moreover the ordering strategies introduced in ADE seem to improve the performances of the only already known asynchronous variant of DE (the Dynamical Differential Evolution Strategy)I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
